Loading Intern Dataset file.

nsc_prospectives = read.csv("./Intern Dataset.csv",header = TRUE)

#str(nsc_prospectives)
#prospectives_from_usl = nsc_prospectives[nsc_prospectives$league=="USL Championship (USA)",]
prospectives_from_mls = nsc_prospectives[nsc_prospectives$league=="MLS (USA)",]
#other_prospectives = nsc_prospectives[nsc_prospectives$league==" (USA)",]


# Gathering players to be filled in the reserve roster spot.

#prospectives_from_usl = prospectives_from_usl[prospectives_from_usl$Age<23,]

Downloading MLS Players’ salary data from American Soccer Analaysis website

suppressMessages(library("htmltab"))

salary_table = htmltab("https://www.americansocceranalysis.com/sept-13-2019",which = 7) 
salary_table$`Base Salary`= as.double(gsub("[\\$,]","",salary_table$`Base Salary`))
salary_table$`Guaranteed Compensation`= as.double(gsub("[\\$,]","",salary_table$`Guaranteed Compensation`))
#fix(salary_table)

# MLS players with Guaranteed Compensation less than $400K.
mls_players_under_400k = salary_table[salary_table$`Guaranteed Compensation`<= 400000.00,]
remove(salary_table)

Gathering Nationality info of USL Players from transfermarket website.

# 
# usl_foreign_players = htmltab::htmltab("https://www.transfermarkt.co.in/usl-pro/gastarbeiter/wettbewerb/USL/saison_id/gesamt",which = 4)
# 
# 
# usl_foreign_players$Player = gsub("á","á",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("é","é",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("ç","ç",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("Ã","í",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("íº","ú",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("í³","ó",usl_foreign_players$Player)
# 
# # usl_foreign_players$Player = gsub("á","a",usl_foreign_players$Player)
# # usl_foreign_players$Player = gsub("é","e",usl_foreign_players$Player)
# # usl_foreign_players$Player = gsub("ç","c",usl_foreign_players$Player)
# # usl_foreign_players$Player = gsub("Ã","i",usl_foreign_players$Player)
# # usl_foreign_players$Player = gsub("iº","u",usl_foreign_players$Player)
# # usl_foreign_players$Player = gsub("í³","o",usl_foreign_players$Player)
# 
# 
# usl_foreign_players$Player = gsub("Goalkeeper","",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("Right-Back","",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("Centre-Back","",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("Left-Back","",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("Defensive Midfield","",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("Right Midfield","",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("Central Midfield","",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("Left Midfield","",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("Attacking Midfield","",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("Right Winger","",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("Centre-Forward","",usl_foreign_players$Player)
# usl_foreign_players$Player = gsub("Left Winger","",usl_foreign_players$Player)

suppressMessages(library("dplyr"))
suppressMessages(library("tidyr"))

# usl_foreign_players =   usl_foreign_players %>% separate(Player,c("firstName","lastName")," ",extra = "merge" )
#usl_foreign_players_copy = usl_foreign_players
prospectives_from_usl = read.csv("./u23_players_2019_with_nationalities.csv",header = TRUE,stringsAsFactors=FALSE)

MLS Players from the dataset, under $400K GC

prospectives_from_mls = left_join(prospectives_from_mls,mls_players_under_400k,by = c("firstName" = "First Name", "lastName" = "Last Name"))
prospectives_from_mls = na.omit(prospectives_from_mls)

remove(mls_players_under_400k)

Joining dataframes of players’ on pitch data and Nationality

mls_players_2019_nationalities <- read.csv("mls_players_2019_nationalities.csv",header = TRUE)
prospectives_from_mls = left_join(prospectives_from_mls,mls_players_2019_nationalities,by = c("firstName"="firstName","lastName"="lastName"))

remove(mls_players_2019_nationalities)

Now we have two dataframes

1) u23prospectives_from_usl = Prospectives from USL under the age 24 for 2020 season.

2) mls_prospectives_under_400k = Prospectives from MLS with GC less than or equal to $400K.

Computing Custom metrics from the dataset.

addMetrics = function(df){
xGperShot = round(df$xG/df$Shot,2)
xAper90 = round((df$xA/df$Min)*90,2)
xGper90 = round((df$xG/df$Min)*90,2)
xAGper90 = round(xAper90 + xGper90,2)
Shotsper90 = round((df$Shot/df$Min)*90,2)
Goalsper90 = round((df$Goal/df$Min)*90,2)
Asstper90 = round(df$Ast/df$Min*90,2)
chancesper90 = round((df$ChncOpnPl+df$ChncSetPl)/df$Min*90,2)
xAGperChance = round((df$xA + df$xG)/(df$ChncOpnPl+df$ChncSetPl),2)
Intper90 = round(df$Int/df$Min*90,2)
Tklper90 = round(df$Tckl/df$Min*90,2)
MinperAG = round(df$Min/(df$Goal+df$Ast),2)
TklAcc = round(df$Tckl/df$TcklAtt*100,2)
df$X1v1. = as.numeric(gsub("%","",df$X1v1.))/100
df = cbind(df,MinperAG,xAper90,xGper90,xAGper90,Shotsper90,Goalsper90,Asstper90,chancesper90,xAGperChance,xGperShot,Intper90,Tklper90,TklAcc)
return(df)
}


usl = prospectives_from_usl#[prospectives_from_usl$Position=="Centre Forward",]
usl = addMetrics(usl)
mls = prospectives_from_mls#[prospectives_from_mls$"Position.x"=="Centre Forward",]
mls = addMetrics(mls)

mls$Country[mls$player=="M. Azira"]="Uganda"
mls$Country[mls$player=="Z. Brault-Guillard"]="Cuba"
mls$Country[mls$lastName=="Blessing"]="USA"

Analysing Centre Forwards

Dumbbell graph for xG/90 and G/90 - MLS CFs

library(plotly)

data = mls[mls$Position.x=="Centre Forward",]
data$player <- factor(data$player, levels = data$player[order(data$Goalsper90)])

#m = 
plot_ly(data, color = I("gray70"),
                text = ~paste(player,'<br>',"MLS",
                              '<br><b>xG/90:</b> ',round(xGper90,2),
                      '<br><b>Goals/90:</b> ',round(Goalsper90,2)),
        hoverinfo = 'text'
        ) %>%
  add_segments(x = ~xGper90, xend = ~Goalsper90, y = ~player, yend = ~player, showlegend = FALSE) %>%
  add_markers(x = ~xGper90, y = ~player, name = "xG/90", color = I("orange")) %>%
  add_markers(x = ~Goalsper90, y = ~player, name = "Goals/90", color = I("blue")) %>%
  layout(
    title = "xG/90 and G/90 - MLS CFs",
    paper_bgcolor='rgb(252, 230, 248)',
    plot_bgcolor='rgb(230, 239, 255)',
    xaxis = list(title = "xG/90 <-----> G/90",showgrid = FALSE,zeroline=FALSE),
    yaxis = list(title = "Centre-Forwards"),
    margin = list(l = 65),legend = list(orientation = 'v')
  )

Dumbbell graph for xG/90 and G/90 - USL CFs

data = usl[usl$Position=="Centre Forward",]
data$player <- factor(data$player, levels = data$player[order(data$Goalsper90)])


#u = 
plot_ly(data, color = I("gray70"),
                text = ~paste(player,'<br>',"USL",
                              '<br><b>xG/90:</b> ',round(xGper90,2),
                      '<br><b>Goals/90:</b> ',round(Goalsper90,2)),
        hoverinfo = 'text'
        ) %>%
      add_segments(x = ~xGper90, xend = ~Goalsper90, y = ~player, yend = ~player, showlegend = FALSE) %>%
      add_markers(x = ~xGper90, y = ~player, name = "xG/90", color = I("orange")) %>%
      add_markers(x = ~Goalsper90, y = ~player, name = "Goals/90", color = I("blue")) %>%
      layout(
        title = "xG/90 and G/90 - USL CFs",
        paper_bgcolor='rgb(252, 230, 248)',
        plot_bgcolor='rgb(230, 239, 255)',
        xaxis = list(title = "xG/90 <-----> G/90",showgrid = FALSE,zeroline=FALSE),
        yaxis = list(title = "Centre-Forwards"),
        margin = list(l = 65),legend = list(orientation = 'v')
      )

Dumbbell graph for xG/90 and G/90 - MLS + USL CFs

data = usl[usl$Position=="Centre Forward",c("xGper90","Goalsper90","player","league")]
data = rbind(mls[mls$Position.x=="Centre Forward",c("xGper90","Goalsper90","player","league")],data)
data$player <- factor(data$player, levels = data$player[order(data$Goalsper90)])


#u = 
plot_ly(data, color = I("gray70"),
        text = ~paste(player,'<br>',
                      ifelse(data$league=="MLS (USA)",
                             paste("MLS"),
                             paste("USL")),
                  '<br><b>xG/90:</b> ',round(xGper90,2),
                      '<br><b>Goals/90:</b> ',round(Goalsper90,2)),
        hoverinfo = 'text'
        ) %>%
      add_segments(x = ~xGper90, xend = ~Goalsper90, y = ~player, yend = ~player, showlegend = FALSE) %>%
      add_markers(x = ~xGper90, y = ~player, name = "xG/90", color = I("orange")) %>%
      add_markers(x = ~Goalsper90, y = ~player, name = "Goals/90", color = I("blue")) %>%
      layout(
        title = "xG/90 and G/90 - MLS and USL CFs",
        paper_bgcolor='rgb(252, 230, 248)',
        plot_bgcolor='rgb(230, 239, 255)',
        xaxis = list(title = "xG/90 <-----> G/90",showgrid = FALSE,zeroline=FALSE),
        yaxis = list(title = "Centre-Forwards "),
        margin = list(l = 65),legend = list(orientation = 'v')
      )

MLS Centre Forwards scatterlplot

plot_ly(data = mls[mls$Position.x=="Centre Forward",], 
        x = ~xGperShot,
        y = ~Shotsper90, type = "scatter",mode = "markers",text = ~paste(player,'<br>',Position.x,'<br><b>Goals/90:</b> ',round(Goalsper90,2)),hoverinfo = 'text',
        color = ~Goalsper90,size = ~Goalsper90,
        marker = list(#size = 10,
          #color = ~Goalsper90,
          line = list(color = 'rgba(152, 0, 0, .8)',
                      width = 1))
) %>%
  layout(title = 'Shot Quality vs Shot Quantity (MLS CFs)',
         paper_bgcolor='rgb(252, 230, 248)',
         plot_bgcolor='rgb(230, 239, 255)',
         xaxis = list(title = "Shot Quality  (xG/Shot)",linecolor = toRGB("black"),showgrid = FALSE),
         yaxis = list(title = "Shot Quantity (Shots/90)",linecolor = toRGB("black"),showgrid = FALSE)
         )

USL Centre Forwards scatterlplot

plot_ly(data = usl[usl$Position=="Centre Forward",],
        x = ~xGperShot, y = ~Shotsper90, 
        type = "scatter",mode = "markers",
        text = ~paste(player,'<br>',Position,'<br><b>Goals/90:</b> ',round(Goalsper90,2)),
        hoverinfo = 'text',
        colors = "RdYlGn",  color = ~Goalsper90,size = ~Goalsper90,
        marker = list(color = ~Goalsper90,
                      line = list(color = 'black',width = 1))
        ) %>%
    layout(title = 'Shot Quality vs Shot Quantity (USL CFs)',
         paper_bgcolor='rgb(252, 230, 248)',
         plot_bgcolor='rgb(230, 239, 255)',
         xaxis = list(title = "Shot Quality  (xG/Shot)",linecolor = toRGB("black"),showgrid = FALSE),
         yaxis = list(title = "Shot Quantity (Shots/90)",linecolor = toRGB("black"),showgrid = FALSE)
         )

All Centre Forwards scatterlplot

data = mls[mls$Position.x=="Centre Forward",c("league","xGperShot","Shotsper90","player","Goalsper90")]
data = rbind(usl[usl$Position=="Centre Forward",c("league","xGperShot","Shotsper90","player","Goalsper90")],data)

plot_ly(data ,
        x = ~xGperShot, y = ~Shotsper90,
        type = "scatter",mode = "markers",
        text = ~paste(player,'<br>',
                      ifelse(data$league=="MLS (USA)",
                             paste("MLS"),
                             paste("USL")),
                      '<br><b>Goals/90:</b> ',round(Goalsper90,2)),
        hoverinfo = 'text',
        color = ~Goalsper90,size = ~Goalsper90,colors = "RdYlGn",
        marker = list(line = list(color = 'rgba(0, 0, 0, .8)',width = 1))
) %>%
  layout(title = 'Shot Quality vs Shot Quantity (MLS + USL CFs)',
         paper_bgcolor='rgb(252, 230, 248)',
         plot_bgcolor='rgb(230, 239, 255)',
         xaxis = list(title = "Shot Quality  (xG/Shot)",linecolor = toRGB("black"),showgrid = FALSE),
         yaxis = list(title = "Shot Quantity (Shots/90)",linecolor = toRGB("black"),showgrid = FALSE)
  )

Radar Chart Template - Centre Forward

library(fmsb)

radarCF = function(data)
{
  #print(data)
  #plot.new()
  
  par(mar = c(1,1,1.3,1))
  #par(mai = c(1,1,1,1))
  par(mfrow=c(9,4))
  plot.new()
  plot.new()
  plot.new()
  plot.new()
  for(i in 1:nrow(data))
  {
    data1 <- rbind(apply(data[c("xGperShot","Shotsper90","X1v1.","xAGper90","xAGperChance","Goalsper90")],2,max) ,
                   apply(data[c("xGperShot","Shotsper90","X1v1.","xAGper90","xAGperChance","Goalsper90")],2,min)  ,
                   data[i,c("xGperShot","Shotsper90","X1v1.","xAGper90","xAGperChance","Goalsper90")])
    #print(data$player[i])
    #print(data1)
    radarchart(data1, axistype=1 , 
               
               # Orange for Domestic , Blue for International Players
               pcol = ifelse(data$Country[i]=="USA",rgb(0.98,0.55,0.01,0.9),rgb(0.1,0.1,0.9,0.7)),
               pfcol = ifelse(data$Country[i]=="USA",rgb(0.98,0.55,0.01,0.3),rgb(0.1,0.2,0.9,0.3)),
               
               #custom polygon
               plwd=2 , 
               
               vlabels =c("xG/Shot","Shots/90","1v1Acc","xAG/90","xAG/Chan","Goals/90"),vlcex=1 ,
               
               #custom the grid
               cglcol="grey", cglty=1, axislabcol="brown", caxislabels= NULL, calcex= 0.6,#, cglwd=0.2,
               
               #custom labels
                
               title = ifelse(data$league[i]=="MLS (USA)",
                              paste(data$player[i],"(MLS)"),
                              paste(data$player[i],"(USL)")),              
               centerzero = TRUE
    )
  }
  mtext("Centre Forwards - Radar Chart",side=3,outer=TRUE,padj=5,cex = 3)
  
}


CF = rbind(usl[usl$Position=="Centre Forward",c("player","league","Country","xGperShot","Shotsper90","xAGperChance","Goalsper90","xAGper90","X1v1.")]
  ,mls[mls$Position.x=="Centre Forward",c("player","league","Country","xGperShot","Shotsper90","xAGperChance","Goalsper90","xAGper90","X1v1.")])

radarCF(CF)

Analysing Central Midfielders

xAG/90 vs Chances/90 - MLS Central Midfielders (Attack-minded)

# xAG/90 vs Chances/90 (MLS CMs)

plot_ly(data = mls[mls$Position.x=="Central Midfielder",],
        x = ~xAGper90,
        y = ~chancesper90, type = "scatter",mode = "markers",
        text = ~paste(player,'<br>',Position.x,'<br><b>Passing Acc:</b> ',round(Pass.,2)),
        hoverinfo = 'text',
        color = ~Pass.,size = ~Pass.,
        marker = list(line = list(color = 'rgba(152, 0, 0, .8)',width = 1))
      ) %>%
  layout(title = 'xAG/90 vs Chances/90 (MLS CMs)',
                  paper_bgcolor='rgb(252, 230, 248)',
         plot_bgcolor='rgb(230, 239, 255)',
         xaxis = list(title = "Expected Contributions Per Match  (xAG/90)",
                      linecolor = toRGB("black"),zeroline = FALSE),
         yaxis = list(title = "Chances Created Per Match  (Chances/90)",
                      linecolor = toRGB("black"),zeroline = FALSE))

xAG/90 vs Chances/90 - USL Central Midfielders (Attack-minded)

data = mls[mls$Position.x=="Central Midfielder",]
data = rbind(data,mls[mls$Position.x=="Centre Attacking Midfielder",])
data = rbind(data,mls[mls$Position.x=="Defensive Midfielder",])

plot_ly(
  data = usl[usl$Position=="Central Midfielder",], 
        x = ~xAGper90,
        y = ~chancesper90, type = "scatter",mode = "markers",
        text = ~paste(player,'<br>',Position,'<br><b>Passing Acc:</b> ',round(Pass.,2)),
        hoverinfo = 'text',
        color = ~Pass.,colors = "RdYlGn",size = ~Pass.,
        marker = list(line = list(color = 'rgba(152, 0, 0, .8)',width = 1))
      ) %>%
  layout(title = 'xAG/90 vs Chances/90 (USL CMs)',
                  paper_bgcolor='rgb(252, 230, 248)',
         plot_bgcolor='rgb(230, 239, 255)',
         xaxis = list(title = "Expected Contributions Per Match  (xAG/90)",
                      linecolor = toRGB("black"),zeroline = FALSE),
         yaxis = list(title = "Chances Created Per Match (Chances/90)",
                      linecolor = toRGB("black"),zeroline = FALSE))

xAG/90 vs Chances/90 - All Central Midfielders (Attack-minded)

# xAGperChance vs Chances/90 (All CMs) (Attacking CMs)
data = usl[usl$Position=="Central Midfielder",c("player","xAGperChance","chancesper90","Pass.","league")]
data = rbind(mls[mls$Position.x=="Central Midfielder",c("player","xAGperChance","chancesper90","Pass.","league")],data)


plot_ly(
  data , 
        x = ~xAGperChance,
        y = ~chancesper90, type = "scatter",mode = "markers",
        text = ~paste(player,'<br>',
                      ifelse(data$league=="MLS (USA)",
                             paste("MLS"),
                             paste("USL"))
                      ,'<br><b>Passing Acc:</b> ',round(Pass.,2)),
        hoverinfo = 'text',
        color = ~Pass.,colors = "RdYlGn",size = ~Pass.,
        marker = list(line = list(color = 'rgba(152, 0, 0, .8)',width = 1))
      ) %>%
  layout(title = 'xAGperChance vs Chances/90 (MLS + USL CMs)',
         xaxis = list(title = "Expected Contributions Per Chance created  (xAGperChance)",
                      linecolor = toRGB("black"),zeroline = FALSE,showgrid=FALSE),
         paper_bgcolor='rgb(252, 230, 248)',
         plot_bgcolor='rgb(230, 239, 255)',
         yaxis = list(title = "Chances Created Per Match (Chances/90)",
                      linecolor = toRGB("black"),zeroline = FALSE,showgrid=FALSE))

Radar Chart Template - Central Midfielder

radarCM = function(data)
{
  #print(data)
  #plot.new()
  par(mar = c(1,1,1.3,1))
  #par(mai = c(1,1,1,1))
  par(mfrow=c(11,4))
  plot.new()
  plot.new()
  plot.new()
  plot.new()
  for(i in 1:nrow(data))
  {
    data1 <- rbind(apply(data[c("xAGper90","chancesper90","xAGperChance","Pass.","Intper90","TklAcc","Recovery","X1v1.")],2,max) ,
                   apply(data[c("xAGper90","chancesper90","xAGperChance","Pass.","Intper90","TklAcc","Recovery","X1v1.")],2,min)  ,
                   data[i,c("xAGper90","chancesper90","xAGperChance","Pass.","Intper90","TklAcc","Recovery","X1v1.")])
    #print(data$player[i])
    #print(data1)
    radarchart(data1, axistype= 1 , 
               
               # Orange for Domestic , Blue for International Players
               pcol = ifelse(data$Country[i]=="USA",rgb(0.98,0.55,0.01,0.9),rgb(0.1,0.1,0.9,0.7)),
               pfcol = ifelse(data$Country[i]=="USA",rgb(0.98,0.55,0.01,0.3),rgb(0.1,0.2,0.9,0.3)),
               
               
               vlabels = c("xAG/90","Chn/90","xAG/Chn","PassAcc","Int/90","TklAcc","Rec","1v1Acc"),
               
               #custom polygon
               plwd=2 , 
               
               #custom the grid
               cglcol="grey", cglty=1, axislabcol="brown", caxislabels= NULL, calcex= 0.6,#, cglwd=0.2,
               
               title = ifelse(data$league[i]=="MLS (USA)",
                              paste(data$player[i],"(MLS)"),
                              paste(data$player[i],"(USL)")),
               
               #custom labels
               vlcex=1 , cex.main= 1.2,centerzero = TRUE
    )
  }
    mtext("Central Midfielders - Radar Chart",side=3,outer=TRUE,padj=5,cex = 3)

}


CM = rbind(usl[usl$Position=="Central Midfielder",c("player","league","Country","xAGper90","chancesper90","xAGperChance","Pass.","Intper90","TklAcc","Recovery","X1v1.")]
           ,mls[mls$Position.x=="Central Midfielder",c("player","league","Country","xAGper90","chancesper90","xAGperChance","Pass.","Intper90","TklAcc","Recovery","X1v1.")])
radarCM(CM)

Analysing Right Backs

Radar Chart Template - Right Back

radarRB = function(data)
{
  #print(data)
  #plot.new()
  par(mar = c(1,1,1.3,1))
  #par(mai = c(1,1,1,1))
  par(mfrow=c(7,4))
  plot.new()
  plot.new()
  plot.new()
  plot.new()
  for(i in 1:nrow(data))
  {
    data1 <- rbind(apply(data[c("xAGper90","xAGperChance","chancesper90","Recovery","TklAcc","Intper90","X1v1.")],2,max) ,
                   apply(data[c("xAGper90","xAGperChance","chancesper90","Recovery","TklAcc","Intper90","X1v1.")],2,min)  ,
                   data[i,c("xAGper90","xAGperChance","chancesper90","Recovery","TklAcc","Intper90","X1v1.")])
    #print(data$player[i])
    #print(data1)
    radarchart(data1, axistype= 1 , 
               
               # Orange for Domestic , Blue for International Players
               pcol = ifelse(data$Country[i]=="USA",rgb(0.98,0.55,0.01,0.9),rgb(0.1,0.1,0.9,0.7)),
               pfcol = ifelse(data$Country[i]=="USA",rgb(0.98,0.55,0.01,0.3),rgb(0.1,0.2,0.9,0.3)),
               
               #custom polygon
               plwd=2 , 
               vlabels = c("xAG/90","xAG/Chn","Chn/90","Rec.","TklAcc","Int/90","1v1Acc"),
               
               #custom the grid
               cglcol="grey", cglty=1, axislabcol="brown", caxislabels= NULL, calcex= 0.6,#, cglwd=0.2,
               
               #custom labels
               vlcex=1 ,
               title = ifelse(data$league[i]=="MLS (USA)",
                              paste(data$player[i],"(MLS)"),
                              paste(data$player[i],"(USL)")),

               cex.main= 1.2,centerzero = TRUE
    )
  }
    mtext("Right Back - Radar Chart",side=3,outer=TRUE,padj=5,cex = 3)

}


RB = rbind(usl[usl$Position=="Right Back",c("player","league","Country","xAGper90","xAGperChance","chancesper90","Intper90","TklAcc","Recovery","X1v1.")]
           ,mls[mls$Position.x=="Right Back",c("player","league","Country","xAGper90","xAGperChance","chancesper90","Intper90","TklAcc","Recovery","X1v1.")])
radarRB(RB)

Shortlisted Players

Read “Preference (International/Domestic) - Playing Style”

CF

1.Moumbagna (Intl) - All rounded
2.M Toye (Dom) - All rounded
3.N Daley (Intl) - All rounded

CM

1.Blessing (Dom) - All rounded
2.Lletget (Dom) - Playmaker
3.Jorge Hernandez (Dom) - Attack

RB

1.H Afful (Intl) - Defensive
2.K Rosenberry (Dom) - Defensive
3.R Laryea (Intl) - All rounded

Final Choice

CF : Moumbagna - USL - International Player
CM : Blessing - MLS - Domestic Player
RB : Rosenberry - MLS - Domestic Player